Institute of Health Economics, Medical University of Innsbruck, Innsbruck, Austria.
Institute of Virology, Medical University of Innsbruck, Innsbruck, Austria.
Lancet Microbe. 2023 Aug;4(8):e612-e621. doi: 10.1016/S2666-5247(23)00107-6. Epub 2023 Jun 21.
Correlates of protection could help to assess the extent to which a person is protected from SARS-CoV-2 infection after vaccination (so-called breakthrough infection). We aimed to clarify associations of antibody and T-cell responses after vaccination against COVID-19 with risk of a SARS-CoV-2 breakthrough infection and whether measurement of these responses enhances risk prediction.
We did an open-label, phase 4 trial in two community centres in the Schwaz district of the Federal State of Tyrol, Austria, before the emergence of the omicron (B.1.1.529) variant of SARS-CoV-2. We included individuals (aged ≥16 years) a mean of 35 days (range 27-43) after they had received a second dose of the BNT162b2 (Pfizer-BioNTech) COVID-19 vaccine. We quantified associations between immunological parameters and breakthrough infection and assessed whether information on these parameters improves risk discrimination. The study is registered with the European Union Drug Regulating Authorities Clinical Trials Database, 2021-002030-16.
2760 individuals (1682 [60·9%] female, 1078 [39·1%] male, mean age 47·4 years [SD 14·5]) were enrolled into this study between May 15 and May 21, 2021, 712 (25·8%) of whom had a previous SARS-CoV-2 infection. Over a median follow-up of 5·9 months, 68 (2·5%) participants had a breakthrough infection. In models adjusted for age, sex, and previous infection, hazard ratios for breakthrough infection for having twice the immunological parameter level at baseline were 0·72 (95% CI 0·60-0·86) for anti-spike IgG, 0·80 (0·70-0·92) for neutralising antibodies in a surrogate virus neutralisation assay, 0·84 (0·58-1·21) for T-cell response after stimulation with a CD4 peptide pool, and 0·77 (0·54-1·08) for T-cell response after stimulation with a combined CD4 and CD8 peptide pool. For neutralising antibodies measured in a nested case-control sample using a pseudotyped virus neutralisation assay, the corresponding odds ratio was 0·78 (0·62-1·00). Among participants with previous infection, the corresponding hazard ratio was 0·73 (0·61-0·88) for anti-nucleocapsid Ig. Addition of anti-spike IgG information to a model containing information on age and sex improved the C-index by 0·085 (0·027-0·143).
In contrast to T-cell response, higher levels of binding and neutralising antibodies were associated with a reduced risk of breakthrough SARS-CoV-2 infection. The assessment of anti-spike IgG enhances the prediction of incident breakthrough SARS-CoV-2 infection and could therefore be a suitable correlate of protection in practice. Our phase 4 trial measured both humoral and cellular immunity and had a 6-month follow-up period; however, the longer-term protection against emerging variants of SARS-CoV-2 remains unclear.
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保护相关因素可以帮助评估一个人在接种疫苗后免受 SARS-CoV-2 感染（所谓的突破性感染）的程度。我们旨在阐明 COVID-19 疫苗接种后抗体和 T 细胞反应与 SARS-CoV-2 突破性感染风险的关联，以及测量这些反应是否增强风险预测。
在奥地利蒂罗尔州施瓦茨区的两个社区中心，我们在 omicron（B.1.1.529）变异株出现之前进行了一项开放标签、4 期试验。我们纳入了平均在接种第二剂 BNT162b2（辉瑞-生物技术）COVID-19 疫苗后 35 天（范围 27-43 天）的个体（年龄≥16 岁）。我们量化了免疫参数与突破性感染之间的关联，并评估了这些参数信息是否可以提高风险区分度。该研究在欧盟药品监管机构临床试验数据库注册，2021-002030-16。
2021 年 5 月 15 日至 5 月 21 日，我们在这两个研究中心共招募了 2760 名参与者（1682 名[60.9%]为女性，1078 名[39.1%]为男性，平均年龄 47.4 岁[14.5]岁），其中 712 名（25.8%）有过 SARS-CoV-2 感染史。在中位随访 5.9 个月期间，68 名（2.5%）参与者发生了突破性感染。在调整年龄、性别和既往感染的模型中，基线时免疫参数水平翻倍的突破性感染风险比（HR）分别为：抗刺突 IgG 为 0.72（95%CI 0.60-0.86）、假病毒中和测定中的中和抗体为 0.80（0.70-0.92）、CD4 肽池刺激后的 T 细胞反应为 0.84（0.58-1.21），以及 CD4 和 CD8 肽池刺激后的 T 细胞反应为 0.77（0.54-1.08）。对于使用假型病毒中和测定在嵌套病例对照样本中测量的中和抗体，相应的比值比（OR）为 0.78（0.62-1.00）。在有既往感染的参与者中，抗核衣壳 Ig 的 HR 为 0.73（0.61-0.88）。在包含年龄和性别信息的模型中加入抗刺突 IgG 信息，可使 C 指数提高 0.085（0.027-0.143）。
与 T 细胞反应相反，较高水平的结合抗体和中和抗体与突破性 SARS-CoV-2 感染风险降低相关。抗刺突 IgG 的评估增强了 SARS-CoV-2 突破性感染的预测能力，因此在实践中可能是一种合适的保护相关因素。我们的 4 期试验同时测量了体液免疫和细胞免疫，并进行了 6 个月的随访；然而，对 SARS-CoV-2 新兴变异株的长期保护作用仍不清楚。
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